Add Registered Model Alias Endpoints and Update RegisteredModel/ModelVersion Payloads

[arpitjasa-db]

Related Issues/PRs

#8001

What changes are proposed in this pull request?

Add SetRegisteredModelAlias, DeleteRegisteredModelAlias, and GetModelVersionByAlias methods to file_store, rest_store, and sqlalchemy_store. Also update RegisteredModel payload to have an aliases field that returns a map of aliases to version numbers, and ModelVersion payload to have an aliases field that returns a list of aliases associated with the version.

How is this patch tested?

• Existing unit/integration tests
• New unit/integration tests
• Manual tests (describe details, including test results, below)

Does this PR change the documentation?

• No. You can skip the rest of this section.
• Yes. Make sure the changed pages / sections render correctly in the documentation preview.

Release Notes

Is this a user-facing change?

• No. You can skip the rest of this section.
• Yes. Give a description of this change to be included in the release notes for MLflow users.

Add SetRegisteredModelAlias, DeleteRegisteredModelAlias, and GetModelVersionByAlias methods to file_store, rest_store, and sqlalchemy_store. Also update RegisteredModel payload to have an aliases field that returns a map of aliases to version numbers, and ModelVersion payload to have an aliases field that returns a list of aliases associated with the version.

What component(s), interfaces, languages, and integrations does this PR affect?

Components

• area/artifacts: Artifact stores and artifact logging
• area/build: Build and test infrastructure for MLflow
• area/docs: MLflow documentation pages
• area/examples: Example code
• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• area/models: MLmodel format, model serialization/deserialization, flavors
• area/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templates
• area/projects: MLproject format, project running backends
• area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• area/server-infra: MLflow Tracking server backend
• area/tracking: Tracking Service, tracking client APIs, autologging

Interface

• area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
• area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
• area/windows: Windows support

Language

• language/r: R APIs and clients
• language/java: Java APIs and clients
• language/new: Proposals for new client languages

Integrations

• integrations/azure: Azure and Azure ML integrations
• integrations/sagemaker: SageMaker integrations
• integrations/databricks: Databricks integrations

How should the PR be classified in the release notes? Choose one:

• rn/breaking-change - The PR will be mentioned in the "Breaking Changes" section
• rn/none - No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" section
• rn/feature - A new user-facing feature worth mentioning in the release notes
• rn/bug-fix - A user-facing bug fix worth mentioning in the release notes
• rn/documentation - A user-facing documentation change worth mentioning in the release notes

[mlflow-automation]

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[arpitjasa-db]

Some open questions on the direction of this PR

[arpitjasa-db]

Should I add docs to this PR or in a follow-up PR? It's already rather large and don't want to make it too big, but will follow best practices.

[BenWilson2]

I'd leave that for a follow up ;)

[BenWilson2]

Looks like you'll have to override these methods in mlflow/store/_unity_catalog/registry/rest_store.py (even with a placeholder of raising a NotImplementedError for the time being)

[harupy]

Left some comments, LGTM once they are resolved!

[BenWilson2]

For this next block of failing tests, I'd try:

1. ON DELETE CASCADE (as you mentioned to me - it's a good thing to try and it SHOULD fix it)
2. If that isn't working, the manual approach will be to handle reverse dependency operations within the DAG of foreign keys (delete the tail ref, then work back to get to the upstream definition)

[BenWilson2]

LGTM! Looks like there are just 2 test-suite related failures. Great work!

[kriscon-db]

LGTM

[harupy]

re-LGTM